Abstract
ABSTRACT Immediately after a significant earthquake, rapid scientific information is critical for response decision-making and estimating secondary hazards, and is a key component of advisories and public communication. Characterization of the fault rupture extent is especially valuable because it strongly controls ground-motion estimates, or tsunami forecasts in offshore settings. The Finite-fault rupture Detector (FinDer) is designed to rapidly estimate location, extent, and orientation of earthquake fault rupture by matching spatial distributions of high-frequency seismic amplitudes with precomputed templates. Under a large public initiative to better prepare for and respond to natural disasters, FinDer is being implemented in New Zealand for rapid source characterization. Here, we report on implementation and performance, including offline and real-time testing using configurations modified for the New Zealand setting. Systematic testing is used to inform guidelines for real-time usage and interpretation. Analysis of rupture parameter recovery when using national network GeoNet stations demonstrates that for moderate (M 6+) onshore earthquakes FinDer can resolve magnitude and location well, and the rupture strike is also well determined for large (M 7+) onshore earthquakes. For near-offshore earthquakes (within 100 km), FinDer can provide reasonable magnitude estimates but cannot determine the location or strike. Real-time testing shows reliable detection for onshore earthquakes of M 4.5+, with reasonable location and magnitude accuracy. First detection times range between 7 and 65 s of earthquake origin, and stable solutions even for large (M 7+) magnitude events are delivered within 2 min. Although the GeoNet seismic network is not optimized for earthquake early warning, this provides a first exploration of network-based capability for New Zealand. Offline testing of significant M 7+ historic earthquakes demonstrates that FinDer’s rupture solutions can be used to improve rapid shaking predictions, and may be used to infer additional directivity and tsunami hazard even for complex events like the 2016 M 7.8 Kaikōura earthquake.
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